POS1596-HPR IMPACT OF THE HEALTH STATUS ON THE WILL TO USE TELEMEDICINE AMONG RHEUMATIC PATIENTS: SECONDARY ANALYSIS OF DATA FROM A GERMAN NATIONWIDE SURVEY
Authors: F. Muehlensiepen, P. Petit, J. Knitza, M. Welcker, N. Vuillerme
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> Telemedicine (TM) is an effective tool to supplement rheumatology care and address staff shortages [1]. A previous study revealed that patients' willingness to try TM is closely connected to their perceived health status [2]. Yet, it is still unclear which factors are associated with patients' motivation to use TM according to the perceived health status. <h3>Objectives</h3> The study aimed to identify factors that determine patients' willingness to try TM (TM-try) and their wish that their rheumatologists offer TM services (TM-wish) according to their perceived health status. <h3>Methods</h3> We conducted a secondary analysis of data from a German nationwide cross-sectional survey among patients with rheumatic and musculoskeletal diseases (RMDs) [3]. Bayesian univariate logistic regression analysis was applied to the data in order to determine which factors were associated with TM-try and TM-wish, respectively. Predictor variables (covariates) studied individually included sociodemographic factors (e.g., age, sex) and health characteristics (e.g., health status). All the variables positively and negatively associated with TM-try and TM-wish in the univariate analyses were then considered for Bayesian model averaging analysis (BMA) after a selection based on the variance inflation factor (≤ 2.5) to identify determinants of TM-try and TM-wish, respectively. <h3>Results</h3> Regarding TM-try, a total of 26 (30.6%) and 45 (27.1%) variables/factors (answers to the 25 questions), out of 85, were found to be positively or negatively associated (ROPE% ≤ 5%) with a perceived okay and bad/very bad health statuses, respectively. Regarding TM-wish, a total of 14 (16.5%) variables/factors (answers to the 25 questions), out of 85, were found to be positively or negatively associated for both a perceived okay and bad/very bad health statuses, respectively. A total of 19 and 13 determinant factors (Figure 1) were identified for TM-try and TM-wish, respectively. Patients with a perceived bad/very bad health status that did not want to try TM were more frequently 60-69 years old, living 10-15 km from the GP's office, being diagnosed with rheumatoid arthritis and had more often less TM knowledge than patients wanting to try TM. Patients with a perceived bad/very bad health status that did wish that TM services were offered by rheumatologist were more frequently older, not documenting their health status and more being diagnosed with osteoporosis than patients wishing that TM services were offered by RM. <h3>Conclusion</h3> Our results indicate that RMD knowledge, age, RMD type, health status documentation and access to technical equipment and infrastructure influence RMD patients' motivation to use telehealth. <h3>References</h3> [1]Miloslavsky EM, Bolster MB. Addressing the rheumatology workforce shortage: A multifaceted approach. Semin Arthritis Rheum. 2020 Aug;50(4):791-796. doi: 10.1016/j.semarthrit.2020.05.009. [2]Muehlensiepen F, Petit P, Knitza J, Welcker M, Vuillerme N. Factors associated with Telemedicine Factors associated with Telemedicine Usage among Rheumatic Patients: Secondary Analysis of Data from a German Nationwide Survey. J Med Internet Res. 2022 Nov 16. doi: 10.2196/40912 [Epub ahead of print] [3]Muehlensiepen F, Knitza J, Marquardt W, May S, Krusche M, Hueber A, et al. Opportunities and Barriers of Telemedicine in Rheumatology: A Participatory, Mixed-Methods Study. Int. J. Environ. Res. Public Health 2021;18(24):13127. doi: 10.3390/ijerph182413127. <h3>Acknowledgements</h3> FM &amp; PP contributed equally and share the first authorship. The authors would like to thank the participants in the survey and all other supporters of TeleRheumaBB. We also owe special gratitude to KV Consult- und Managementgesellschaft mbH, which initiated the study in the first place. The present work is part of the PhD thesis of F.M. (AGEIS, Université Grenoble Alpes, Grenoble, France). <h3>Disclosure of Interests</h3> Felix Muehlensiepen Speakers bureau: Novartis, Paid instructor for: Novartis, Consultant of: Novartis, Grant/research support from: AbbVie, Novartis, Pascal Petit: None declared, Johannes Knitza Speakers bureau: Abbvie, Novartis, Medac, Sanofi, Amgen, UCB, Consultant of: Abbvie, Novartis, Lilly, Medac, BMS, Sanofi, Amgen, Gilead, UCB, ABATON, GSK, Werfen, Vila Health, Böhringer Ingelheim, Janssen, Galapagos, Chugai, Grant/research support from: Abbvie, Novartis, Thermo Fisher, UCB, ABATON, Sanofi, DFG, EIT Health, Martin Welcker Shareholder of:/, Speakers bureau: Abbvie, Actelion, Amgen, Biogen,BMS, Berlin Chemie, Celgene, Galapagos, Gilead, GSK, Hexal, Janssen, Medac, MSD, Mundipharma, Mylan, Novartis, Pfizer, Roche, Sanofi, SOBI, UCB, Consultant of: Abbvie, Actelion, Aescu, Amgen, Cel- gene, Hexal, Janssen, Medac, Novartis, Pfizer, Sanofi, UCB, Grant/research support from: Novartis, Abbvie, Nicolas Vuillerme: None declared.